Meta
Models published by Meta, available through the AnyRouter API. Each can route across multiple upstream providers for availability and price.
Meta's Llama 3.1 70B instruction-tuned model with strong reasoning and multilingual capabilities.
Meta's compact Llama 3.1 8B instruction-tuned model optimized for fast inference and edge deployments.
The Llama 3.2-Vision instruction-tuned models are optimized for visual recognition, image reasoning, captioning, and answering general questions about an image.
Meta's Llama 3.3 70B instruction-tuned model for high-quality chat, reasoning, and coding at a fraction of frontier cost.
Meta's Llama 4 Scout with 17B parameters and 16 experts, featuring native multimodal support with 10M context window via interleaved attention.
Llama Guard 4 is a 12B natively multimodal safety classifier for content safety classification on LLM inputs and responses. It acts as an LLM itself: it generates text indicating whether a prompt or response is safe or unsafe and, if unsafe, lists the violated categories (MLCommons hazards taxonomy S1–S14). Use it as a guardrail/judge hop in front of or behind chat models.
Meta Muse Glimmer 30B is a ~30B dense multimodal instruct model (text and image in, text out) with a 131K context window, chain-of-thought reasoning, and function calling. Available on NVIDIA NIM for chat and agent workflows.
Meta's Muse Spark 1.1 is a multimodal reasoning model built for agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text,a 1M-token context window. The model orchestrates multi-agent workflows — acting as a main agent that plans and delegates or as a subagent — and generalizes zero-shot to new tools, MCP servers, and custom skills. It supports structured output, parallel function calling, built-in searchcitations, and configurable reasoning effort. Availablea. NOTE: currently available to users in the United States only.
Meta's Muse Spark 1.2 is a multimodal reasoning model for complex agentic tasks. It accepts text, images, video, audio, and PDF documents, returns text, and offers a 1M-token context window.
The cost-efficient contributor tier of Meta's multimodal reasoning model Muse Spark 1.3, for experimentation and early-stage agentic and coding workflows.
Meta's Muse Spark 1.3 is a multimodal reasoning model for complex agentic tasks. It accepts text, images, video, audio, and PDF documents, returns text, and offers a 1M-token context window.
Meta's Muse Wonder is a frontier reasoning model for complex personal and professional agentic tasks. It accepts text, images, video, audio and PDF documents and returns text.